Running Head: RESEARCH GRANT PROPOSAL 1

Running head: RESEARCH GRANT PROPOSAL 1

Research Grant Proposal Shawn Kise, MS student, BSN RN NUR 707 Wright State University Table of Contents Cover page …………………………………………………………………………………………………………………..1 Part I – Specific Aims ……………………………………………………………………………………………………….3 Problem Statement …………………………………………………………………………………………………3 Study Variables ……………………………………………………………………………………………………..3 Specific Aims ………………………………………………………………………………………………………..3 Research Questions or Hypotheses ……………………………………………………………………………...3 Potential Funding Source (see Appendix A) …………………………………………………………………...14 Part II – Background and Significance ……………………………………………………………………………………3 Review of the Literature Grid (see Appendix B) ……………………………………………………………….15 Review of the Literature Narrative ………………………………………………………………………………..3 Brief Presentation of the Theory, Theoretical or Conceptual Framework ……………………………………7 Conclusions of the Literature Review Narrative …………………………………………………………………7 Part III – Research Plan …………………………………………………………………………………………………….8 Research Methods and Design …………………………………………………………………………………...8 Setting ……………………………………………………………………………………………………………….8 Sample ………………………………………………………………………………………………………………8 Sampling Plan, including Recruitment Procedures ……………………………………………………………..9 Inclusion/Exclusion Criteria ………………………………………………………………………………………..8 Ethical Consideration (Human Subjects Protection) …………………………………………………………..10 Data Collection Procedures ……………………………………………………………………………………...10 Data Analyses Procedures ………………………………………………………………………………………11 References …………………………………………………………………………………………………………………12 Appendices …………………………………………………………………………………………………………………14 Appendix A – Potential Funding Source ………………………………………………………………………..14 Appendix B – Review of the Literature Grid ……………………………………………………………………15 Appendix C – Human Subjects ~ Informed Consent ………………………………………………………….35 Appendix D – CITI Training Certificate …………………………………………………………………………36 Appendix E – Community Flyer..…………………………………………………………………………………37 Appendix F – USDA Household Food Security Survey Module .…………………………………….38 Specific Aims (Problem statement) – In 2007-2008 the Center for Disease Control and Prevention (CDC) published a report showing the prevalence rate for obesity among women at 35.5% (Flegal, Carroll, Ogden & Curtin, 2010). Ford, Li, Zhao, and Tsai (2010) reported the prevalence of obesity among women at 35.2% and the prevalence of abdominal obesity among women at 61.8% during the years of 2007- 2008. Ogden, Lamb, Carroll, and Flegal (2010), published report in the CDC, found that from 2005- 2008 women of lower education and income were more likely to be overweight. (Background/significance or why the need for another study). Obesity has been on the rise for many years and remains a major threat among lower-income women. Prevalence and trend reports have continuously shown an increase in obesity in women over the past several decades. Flegal, Carroll, Ogden, and Johnson’s (2002) study from 1988 – 1994 and 1999 – 2000 found an increase in obesity in women ages 20 – 74 years. Ford, Li, Zhao, and Tsai (2011), also found significant increases from 1999 – 2008 in abdominal obesity in women. Prior research has examined many specific groups related to obesity, including race, ethnicity, and socioeconomic status. The findings from several studies have shown that obesity is a major concern in lower-income communities and populations; Ahn, Huber, Smith, Ory, and Phillips (2011), Bove and Olson (2006), Cohen, Sturm, Lara, Gilbert, and Gee (2010), and Ford and Dzewaltowski (2011). Based on these findings, further studies are needed to better understand reasons for obesity among lower-income women. The findings will be used to better educate women and provide needed resources to help reduce the obesity trends. (Specific aims or purpose)- The purpose of this quantitative research study is to examine the influence of food security using the U.S. Household Food Security Survey Module, and barriers to physical activity level affects body mass index among low-income women. Food insecurity is described by Ivers and Cullen (2011) as not having access to sufficient, safe, and nutritious food at all times to meet ones dietary needs. Ivers and Cullen have found that food insecurity is associated with obesity, anxiety, and depressive symptoms. In Bove and Olsen’s (2006) study, physical activity was limited to transportation barriers and physical environment. The following research questions were derived from the specific aims: (1) what is the relationship between food insecurity and BMI in low-income adult females in the Dayton, Ohio area? And, (2) what is the relationship between barriers to physical activity and BMI in low-income adult females in the Dayton, Ohio area? The findings from this study will contribute to the study topic and be used to implement a tailored, cultural sensitive, and nurse delivered intervention to reduce obesity among low-income women in the Dayton, Ohio area. Background and Literature Review

Prior research has supported that food insecurity and decreased physical activity positively correlates to higher body mass index (BMI) in low-income women. The terms food insecurity and food security is not understood by many people so it will be clarified what each term means. The United States Department of Agriculture (USDA) (2009) defines food insecurity as “limited or uncertain availability of nutritionally adequate and safe foods or limited or uncertain ability to acquire acceptable foods in socially acceptable ways”, and food security is defined as “access by all members at all times to enough food for an active, healthy life”. The USDA reported that in the year 2010 14.5% of households were food insecure at some point throughout the year. Research has shown that food insecurity is directly related to higher BMI levels in low-income women. Other studies have provided evidence that nutrition education was significant in lower food insecurity in this population. Likewise research has shown that decreased physical activity is directly related to higher BMIs in low-income women. The Centers for Disease Control and Prevention (CDC) report that one-third (33.8%) of US adults are obese (CDC, 2011). The CDC (2011) also states that obesity is caused by an energy imbalance caused by individuals eating too many calories and not getting enough physical activity. This is why research must be done to investigate the factors that cause barriers to physical activity. This literature review will address past research on both variables and show why this research is crucial in lowering obesity rates in low-income women. Townsend, Peerson, Love, Achterberg, and Murphy’s (2001) quantitative study used a theory informed conceptual framework to guide their work. The conceptual framework was stated as food insecurity and its relationship to overweight. They examined food insecurity in the general population and its effects on their weight using the BMI. Data were obtained using the Continuing Survey of Foods Intakes by Individuals from 1994, 1995, and 1996. Participants who completed the survey had to be 20 years of age or older and given their stated weight, height, and income information. Institutionalized, homeless, and women that were pregnant or lactating were excluded from the study giving a final sample of N=9541. The food insecurity categories related to being overweight and income status was examined with ANOVA and Turkey’s test using a significance level of P<0.05 and logic regression model was used to correlate the probability of participants being overweight with a level of significance being 0.05. The study results revealed that food insecurity correlated to women participants being overweight (P<0.0001, n= 4509), but among the male participants there was no correlation observed (P=0.44, n=4970). Only 34% of the women stated they were food secure and overweight compared to the mildly food insecure which 41% of participants were overweight (P<0.05), and there was a significant increase in the moderate food insecure group with 52% being overweight. Townsend et al. (2001), also reported that lower income levels were related to food insecurity (P<0.0001); with reported income levels being highest in the food secure participants and participants that have lower incomes in the mild food insecurity group, with the moderate food insecurity group having the lowest reported incomes. In a similar study Jilcott, Wall-Basset, Burke, and Moore (2011) examined food insecurity related to BMI in a cross-sectional designed study of low-income women in Pitt County, North Carolina. They recruited women from the Pitt County Department of Social Services waiting area. All participants were enrolled in the Supplement Nutrition Assistance Program (SNAP), and were between the ages of 20 to 64, English speaking, and were the primary food shoppers in the home. Informed consent was obtained by the interviewers; trained research assistants measured height and weight twice to the nearest 0.1cm and 0.1 lb. to assure accuracy. The US Department of Agriculture 18-item core food survey was used to determine food security. To measure perceived stress a 14-item Cohen’s Perceived Stress Scale was used. The majority of women were found to have marginal or low food security. All statistical data were analyzed using SAS version 9.2. The researchers found a positive correlation between perceived stress and food insecurity (r=0.36, P<0.0001), and a positive correlation between food insecurity and BMI (0.18; P<0.05). There was no relationship between perceived stress and BMI in the participants of this study. Food insecurity was also measured in the participants of Dammann and Smith’s (2011) study. This was a cross-sectional design to examine the food related environment, behavior, personal factors and their association with the BMI of low-income women in the Twin Cities metropolitan area of Minnesota. Participants from three different racial/ethnic groups were included. The three racial/ethnic groups were African- American, American Indian, and Caucasian with the average age of 35.4 ± 9.9 years of age. To measure food insecurity in the participants the USDA 18-item Household Food Security Survey Module was used. Height and weight was taken twice to the nearest 0.1 cm and 0.1 kg by a single research assistant. Data analysis were run in SPSS version 17.0. From the total sample (N=367), 74% were reported as having low or very low food security with racial/ethnic identity being associated with food insecurity (p=.032). Racial/ethnic differences were not associated with the mean BMI but were related to BMI categories (p=.039). The majority of the sample (82%) was overweight or obese with a BMI ≥ 25. This study included women who were homeless in which 47.5% of African-American women and 46.5% of Caucasian women reported being homeless as compared to 16.6% of the American Indian women being homeless. These data could be a major variable in the difference of food security between racial/ethnic groups. Ford and Dzewaltowski’s (2011) conducted a multilevel analysis to determine the relationship between neighborhood deprivation, supermarket availability and BMI in low-income women in Kansas that were enrolled in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC). Participants were enrolled in WIC from October 2004 to December of 2006. WIC datasets from clinic visits were used to obtain data for this study. Pre-pregnancy weights were self-reported and post-pregnancy weights were objectively measured at the post-pregnancy WIC clinic visits with the pre and post pregnancy weights highly correlated (Cronbach’s α = 0.95, P< 0.001). The participants were categorized by the type of neighborhood in which they lived and included rural, metropolitan, and micropolitan areas. The Kansas Department of Agriculture retail food establishment list was used to determine supermarket availability for each category. Tract deprivation was determined by a maximum likelihood factor analysis. All data analyses were run in SPSS v. 15.0. The final sample (N=21,166) revealed a positive relationship between tract deprivation and higher BMI in the metropolitan areas with areas of greater deprivation having a higher unit increase in BMI. No association was seen between BMI and tract deprivation of rural areas. There was also no direct association between supermarket availability and BMI. Tract deprivation and supermarket availability are variables or factors that could influence food security and that is the reason for including this study in the review of literature. The research that has been discussed thus far has shown that there are many variables to be considered when looking at the relationship between food insecurity and BMI. The major factors in these studies included racial/ethnic consideration, women receiving supplemental nutrition assistance, neighborhood deprivation, supermarket availability, and behavioral/personal factors. Townsend et al. (2001), Jilcott et al. (2011), and Dammann and Smith (2011) conclude that further research should be continued in this area to get a better understanding of the variables that influence food insecurity which has shown to affect the BMI in low-income women. Dammann and Smith (2011) further report that studies on the factors that were explored in their study would help tailor effective educational and intervention programs for nutrition in this population of low-income women. In a single-blind randomized study using an experimental/intervention and control group, Eicher-Miller, Mason, About, McCabe, and Boushey (2009), showed that an intervention group of low-income women receiving food stamps that received nutrition education significantly improved their food insecurity over a control group (P=.03, P=.04). This intervention group received 5 food stamp education sessions in between completing a pre-test and post-test. The control group completed the same pre and post-test with no intervention. Participants were females older than 18 years of age and head-of-house-hold receiving food stamp assistance (n=219). Chi-square analyses were used to compare participant’s characteristics and analysis of covariance models were used to determine the effects of treatment groups with significance at P≤.05. Data analyses were performed in SAS version 9.1. This study showed that educational programs in this population are beneficial in improving food insecurity for low-income women. We know that limited or no physical activity can affect an individual’s BMI. Research has examined many different variables that cause barriers to physical activity and why physical inactivity is present in low-income women. Further research has been done to exam interventions to increase physical activity and its relationship to women’s health. Cleland, Salmon, Timperio, and Crawford (2010) examined personal, social, and environmental factors that correlate to women of low socioeconomic backgrounds resilience to inactivity. The researchers used the recommendation of at least 30 minutes of moderate intensity physical activity a day on most days of the week as the standard to measure the women in this study. The researchers used a stratified sampling survey to choose 2400 women from low, mid, and high socio-economic strata from 45 different neighborhoods of Melbourne, Australia to receive a mailed survey on physical activity. Another 2400 separate women from the same neighborhoods were chosen in the same manner to receive a mailed survey on nutrition. The respondents who completed the nutrition survey were asked to complete the physical activity survey. In all 1045 women completed the physical activity survey (44% response rate) with 1136 women filling out the nutrition survey (47% response rate), with 509 women completing both the nutrition and physical activity surveys. Physical activity was measured by the International Physical Activity Questionnaire. Chi-squared test and one way analysis were used to determine significance between social, personal, and physical factors and physical activity (P<0.05). Items with a significance of P<0.05 were entered into a multivariable model and displayed in the article. All analyses were done with Stata version 9.2. The results revealed that self-efficacy for walking, high self-efficacy for vigorous physical activity, and enjoyment of walking were significant factors to achieving the recommended physical activity. Higher rates of physical activity were reported when women had a set physical activity routine and were able to fit physical activity into their schedules. For the social factors that were relevant in achieving the recommended physical activity were high social support from friends and colleges, higher levels of social participation, and owning a sports or recreational club membership. The only environmental factor that had an effect on physical activity was having busy streets or roads to cross in order to walk for exercise. Bove and Olson (2006) also conducted a study to investigate several factors of low in-come mothers in rural areas of New York State to understand overweight and obesity from their prospective. Barriers to physical activity, emotional factors, and food security were all addressed among other variables in the study. Participants were required to be 18 years of age and have at least one child 12 years old or younger living in the home with them, and have an annual income of 200% less than the national poverty level. Participants were recruited from the programs of Special Supplement Nutrition Program for Women, Infants, and Children (WIC) and Even Start, a program to help improve rates of family literacy. A sample of 28 women was included in the study. Each woman participated in three in-depth interviews about a year apart from one another, and gave signed consent at the initial interview with all interviews being audio taped. Each participant received a $20 gift card to a local grocery store on the completion of each interview. Open-ended and close-ended questions were used as well as the U.S. Household Food Security Survey. Of the participants, 62% were overweight or obese, 32% normal weight, and 7% were underweight. Lack of transportation was a barrier to physical activity reported by 43% of the participants and was twice as common from the overweight and obese participants. High cost of gas was also stated by many participants as a factor in reducing the amount of their physical activity. Having young children and strollers were all reported as limiting physical activity as well as health problems that limited mobility. Food insecurity status changed throughout the study but was reported by two-thirds of participants in at least one or more of the interview sessions and 57% of participants were reported as having food insecurity at the time of enrollment. Emotional eating was not influenced by food security with 60% stating they over ate do to stress, sadness, boredom, or loneliness. Three-quarters of the overweight and obese participants reported emotional eating while less than half of the normal or underweight participants stated that they eat because of emotional stressors. The participants in the categories of overweight and obese did see their weight as a health concern. This study is important in showing that this population is vulnerable to emotional stressor that can create unwanted eating patterns. Many studies exclude women that are greater than 65 years of age because this elderly population can be perceived as having a different group of factors related to being overweight and obese. Ahn, Huber, Smith, Ory, and Phillips (2011) focused on this population of older adults and the predictors of their BMI’s. Data collection took place in 2006 and a final sample of (n=705) was included in the study. Participants were recruited by those receiving Medicare personal care services or those that were applying for Medicare personal care services in the state of Texas. Participants in this study were required to be 65 years of age or older, have a BMI ≥ 18.5 kg/m2, and have English or Spanish as their primary language. State Medicaid case workers who were trained in the assessment tools were used to collect data. A subset of items from the Community Health Assessment tool, which was also a subset from the Minimum Data Set for Home Care, was used in the data collection. The assessment tool included three main areas: pain, cognitive function, and functional limitations. Activities of daily living (ADL) and instrumental activities of daily living (IADL) were used to measure functional limitations. Pain items were grouped together (Cronbach’s alpha = 0.87) and ADL items were also grouped together (Cronbach’s alpha = 0.87). All data were analyzed using Stata Version 10. Of the participants three-fourths were female and two-thirds were older than 75 years of age with 78% of the sample being overweight (28%) or obese (50%). Obesity was observed most in females (OR = 0.33, P<.001), and less in participants greater than 75 years of age (OR = 0.33, p<.001), participants with higher cognitive function (OR = 0.33, p = .006) and those who were smokers (OR 0.37, p = .012). The final model showed that women were more likely to be overweight (OR = 0.54, p = .016) and to have greater pain (OR = 1.07, p = .033). Smoking was later determined to be non-significant in the analysis. This study reveals that in the elderly population being female, being younger than 75 years old, and having lower cognitive function put you at greater risk for being overweight or obese. This is significant in supporting that low-income women of all ages are being affected by obesity. Eicher-Miller et al. (2009), discussed earlier in this review showed that a nutrition education program was beneficial in improving food security for their low-income women participants. The following two studies revealed that nutrition education programs and programs to increase physical activity also have beneficial results in this population to lower participant’s BMIs. Miles and Panton (2006) conducted a mixed qualitative/quantitative study to investigate BMI in low-income women participating in an intervention to increase their physical activity would be able to complete an intervention and if that intervention would have health benefits. They also examined what the participants perceived as being supporting and constraining in their communities. Participants included in this study were receiving Medicaid benefits, between the ages of 30 and 65, able to tolerate the increase in walking intervention, and have an initial BMI of >25. Women who were already involved in a physical activity program were excluded. The final sample (n=29) included all of these characteristics. Baseline measurements and blood work were done on the initial visit. Participants were asked to increase their total number of steps a day to the recommended amount of 10,000 steps a day. Steps a day were measured by a pedometer each participant received at their first visit and the participants were to keep a log book to record their progress. Measurements and blood tests were repeated every three months for a twelve month period. Each participant was paid $10 at the end of the initial, three-month, six-month, and nine-month visit. At the end of the final visit participants were given $85 for a total of $125 for completing the study whether they increased their number of steps a day or not. Of the 29 participants 25 agreed to be interviewed using an open ended question about their younger days of life and the physical activity they engaged in at that time. Participants were categorized as compliers (participants who increased their number of steps a day by at least 2,000) and non-compliers (participants who did not increase their steps a day by 2,000), with the compliers increasing their average steps a day from 6,306 to 10,870 and non-compliers did not increase their average steps a day (4,929 to 4,742). Older participants were found to be more likely to be non- compliers (p = 0.07). The compliers showed significant results in lowering their BMI at the six, nine, and twelve-month visits from their BMI at the initial and three-month visit. The participants who did not increase their number of steps a day did not show improvements over the course of the study. Barriers or limiting factors to increase the number of steps a day by the participants were chronic health problems, stress, and safety/security concerns. The safety/security concerns were only stated by non- compliers in the study. The compliers mainly report walking in their own neighborhoods or at the mall. Jordan, Freeland-Graves, Klohe-Lehman, Cai, Voruganti, Proffit, Nuss, Milani, and Bohman (2008) conducted a quantitative study to evaluate a nutrition and exercise program in low-income mothers with young children. Their aim in this study was to explore if an educational intervention would assist in weight loss and improve the nutrition attitudes in their participants. The participants were recruited from the WIC program, community centers, and churches. Inclusion criteria for this study was that each participant must be of African-American, white, or Hispanic ethnicity, have a youngest child between 1 and 4 years in age, a BMI >25, be of low-income status (>200% of the poverty index), and be absent of breast feeding. The final sample of n=114 completed the intervention with the researchers reporting an attrition rate of 56%. Each participant gave written consent at the first class of the intervention. The intervention included weekly educational classes on nutrition and exercise for an eight week period. Each participant was asked to report a 24 hour diet recall and a 2 day record of food intake at weeks 0 and 8. Height, weight, body fat percentage, and waist circumference was taken at week 0 and week 8. Nutrition attitudes were assessed using the Nutrition Attitudes Scale which contained 4 subset focus areas: sensory motivators, emotional eating, perceived barriers, and healthful eating. The questionnaire was administered at weeks 0 and 8. The intervention was completed at week 8 and considered the endpoint; there was a subset of 93 participants that were able to make a week 24 reassessment of height, weight, body fat percentage, and waist circumference. The week 24 reassessment was to evaluate whether participants were able to maintain results from the eight week intervention. A group of 33 overweight/obese mothers with the same background characteristics were used as a control group and was not provided with the intervention. The control group provided height, weight, body fat percentage, and waist circumference measurements at week 0 and week 8 only. All statistical data were analyzed using the SPSS software and statistical significance was only shown if the probability was less than .05. The results yielded high significant changes in lowering participants weight (x = -2.7 kg; median, -2.4kg; P<.001), body fat percentage (x = -1.2%; P<.001), and waist circumference (x = -3.5cm; P<.001). Of the participants that completed the intervention 89% lost weight, 1% maintained their weight, and 13% gained weight. At the week 24 reassessment participants again showed significantly lower measurement for weight (x= -2.7; P<.001), body fat percentage (x = -0.8%; P<.01), and waist circumference (x = -12.1cm; P<.001) compared to their baseline measurements. Most all the participants (>90%) stated that they learned a great deal from the intervention regardless of their results. The participants reported that the in class exercises, weekly weigh-ins, and use of a pedometer were the most useful components of the intervention. These two studies are significant in showing that educational and exercise programs are beneficial in the women with low-income population. Conclusion and Theoretical Framework This literature review captures the importance in research on the variables that affect the BMIs and ultimately the overall health in low-income women. The variables in this research proposal (food insecurity and barriers to physical activity) may change significantly from location to location. Whether a study is completed nationally or by state, county, or city the factors that can lead to food insecurity and barriers of physical activity can be very different from setting to setting. For example one city might have an excellent public transportation system that women can use to get a place where they feel comfortable and safe to exercise or have access to grocery stores with healthy food options as compared to another city that may have limited or no public transportation for these women. This is an important reason to continue research in this area. Researchers have also indicated the importance of investigating these variables to provide data that will help healthcare workers develop better educational programs on nutrition and exercise or work with the area officials to address the needs of this population. Research was provided to show that educational programs and interventions in this population had significant results in the participants of their studies. This supports that further research on these variables to provide better education and programs for this population will have an impact in lowering the rates of obesity in low-income women. Social Cognitive Theory was used as a frame work in two of these studies. This framework along with Nola Pender’s Health Promotion Model will be used in guiding this study. Food insecurity and its relationship to overweight takes into account four areas of a person’s life that can affect food security: personal demographics, socio-economic status, use of government assistance, and the environment. The design of the health promotion model is to help increase the patient’s level of wellbeing and takes into account the multivariable nature of the person and the environment in which they live to gain better health. Pender’s Health Promotion Model and food insecurity and its relationship to overweight to conduct this research is expected to yield data that will provide better education and programs to better serve the low-income women in the Dayton, Ohio area and promote health and wellbeing.

Research Plan

Research Method and Design

This quantitative, descriptive correlational study will examine the correlation between food insecurity and barriers to physical activity to body mass index among low-income women in the Dayton area. According to Polit and Beck (2012), quantitative descriptive correlational design is most appropriate for this study because description correlational research is to describe relationships among variables rather than support inferences of causality.

Setting

This study will take place in the Medicaid office located in the Job and Family Services agency building in a moderate-size city in the Midwest. The agency serves approximately 48,000 individuals receiving Medicaid benefits in the county. This county has four Women, Infant, and Children (WIC) offices that will be used for this study.

Population

All low-income women in this moderate sized county are the accessible population for this study. The target population will include low-income women who use the four WIC offices in the stated county and women who use the county Job and Family Services Medicaid office during the data collection period for this study. These offices serve many low-income women every month throughout the year. Therefore the projected number of 48 women should be able to be recruited in an appropriate amount of time.

Sampling Procedures

Inclusion criteria for this study are as follows: (1) participants must be female; (2) be between the ages of 18 to 65 years of age; and (3) must have a total household income up to 185% of the Federal Poverty Income Guidelines. The exclusion criteria include: (1) anyone who is not female; (2) those who are < 18 and > 65 years of age; and (3) any female with a total household income of more than 185% of the Federal Poverty Income Guidelines.

The sampling plan is a purposive, convenience sample. Snowball sampling will also be used if the researcher is unable to obtain the projected number of participants into the study. The total number of participants in this study is 30. Oversampling will occur by 60% to account for attrition (N = 48). Oversampling by 60% was determined by the high attrition rates for mail surveys.

Recruitment of participants will be done using a community flyer and by the staff of the Medicaid office located within the Job and Family Services building and the staff of the four WIC offices in the county. These five offices provide services to low-income women that live in the moderate-sized Midwestern city. In the year 2007, 15.2% of all residents in the county received Medicaid with a total number of 84,082 participants (Montgomery County, 2008; Ohio Department of Job and Family Services, 2008). The county currently has four WIC office locations that serve some of the nearly 300,000 WIC participants in Ohio. After contact with the directors of the Medicaid and WIC programs to introduce the proposed study, the researcher will gain permission to place signs outside of the offices of the four WIC locations and the Medicaid office located within the Job and Family Services building, introducing the study. With the permission of the director of the Job and Family Services, flyers will be placed on all bulletin boards in the Job and Family Services building. See Appendix E for a copy of the flyer. The researcher will invite all staff at these offices to introduce the study to eligible women when they come in for WIC and Medicaid services. The staff will apprise the women of the study during or after the appointment. Staff conducting the appointments will be instructed to at the end of the appointment, if not already discussed, to ask the client if they had a chance to review the study flyer and if they would like to be a participant. The staff will be instructed by the researcher to inform the women of the time commitment it will take to complete the study. If the woman states that she wants to be a participant then she will be provided a quiet and private place to fill out the study material. After receiving informed consent, a staff member will administer the study packet and allow her to fill out the material in private. The study packet will contain a thorough instruction page on how to complete the study, a demographic questionnaire, questionnaire on food security, questionnaire on barriers to physical activity, and a letter thanking them for completing the questionnaires. The letter will also include the researchers contact information if the participants have any questions or concerns. When the women are done completing the questionnaires they will place them into a large envelope provided and seal the contents inside. The office staff will be instructed to direct the women to place the envelope into a locked box that will be located at each office. The locked box will only be assessable to the researcher. If there is a woman that would like to be a participant but does not have time to complete the study that day, staff will provide a contact card for the women to fill out and direct them to place it in the same locked box as the completed study packets. The researcher will collect the completed study packets and contact cards every Friday during the data collection period. The research will use the contact cards to make phone contact with the women who are interested in participating. The socio-demographic questions will be discussed with the women by the researcher, and they will be asked if they are comfortable sending this personal information by mail to the researcher. The study information will be given over the phone by the researcher and the women will be asked permission to send the study material to their home. The envelopes will be addressed to the potential participant and contain no information on the contents inside. The women who received the study material by mail will be provided a pre-addressed and pre-stamped envelope to return the study material to the researcher. The completed study material will be sent to a post office box that only the researcher will have access to. The researcher will collected the completed study packets from the post office box frequently throughout the data collection period. Women who contact the researcher by e-mail or phone who have seen the community flyer will be recruited in the same manner. Women who receive the study material by mail will be sent a reminder card two weeks after the mailing of the study packet unless the completed study material has been received. Upon receiving the completed study material from the participants, the researcher will send a thank you post card to the participants including the researcher’s contact information to receive a $10 VISA gift card for their participation in the study.

Ethical Considerations

Approval will be obtained through the Wright State University Institutional Review Board as well as from the directors overseeing the WIC and Medicaid programs. The researcher has recently completed the CITI training for “Human Subjects”, required for all studies. A copy of the certification will be provided in appendix D. No one other than the researcher, data entry clerk, and the Statistical Consultation Center at Wright State University will have access to these data. The confidentiality of participants will be maintained at all times. The completed packets by the participants will be mailed to a post office box only accessible to the researcher. The researcher will retrieve all study packets from the post office box and transport them to my office where they will be kept in a locked file cabinet which only the researcher will have access to. All data will be assigned a security number so that the participants cannot be connected to the data and the researcher will be the only one to have access to the participant’s names. All data stored on by computer will be protected by a security password and only the security numbers (not actual names) will be used in data entry into the computer. Anonymity for all participants will be kept. All participants’ identities will be protected and at no time will they be available to anyone other than the researcher. The list of participants will be destroyed on the completion of the study. Questionnaires will not contain any information that can connect the data to the participants. The procedure will be explained in writing to all participants and they will be informed that they can forego any questions they do not feel comfortable answering. Risks: By completing this survey the women will not be exposed to any know physical risk. There is a risk for these women to experience psychological stress or mild anxiety when taking this survey due to questions addressing sensitive subjects for many women. Benefits: The information gained in this study will provide a better understanding about food insecurity and the barriers to physical activity in low-income women in this moderate-sized city in the Midwest. The findings of this study will be used to develop and implement a tailored intervention to improve BMI related to food insecurity and barriers to physical activity among women in this moderate-sized Midwestern city. Each participant will receive the $10 VISA gift card for participation in the study. Explanation of the procedure, risks, benefits, confidentiality, and the right not to participate will be in writing on the informed consent that all participants must sign and return with their study questionnaires.

Data Collection Procedures

The following instruments will be used to measure the study variables in this grant proposal. The United States Department of Agriculture’s (USDA) 18-item Household Food Security Survey Module will be used to measure food security. The USDA guidelines will be used in scoring participants responses in this survey. Based on the literature review this is a validated tool and was reviewed by field experts for face validity. No other reliability or validity measures were given. Participants will be given a study packet that will include an informed consent, demographic survey, questionnaire to assess food insecurity, and a 15-item questionnaire to assess barriers to physical activity. A 9-item socio-demographic questionnaire will also be included. The socio-demographic questionnaire will ask participants their age, race/ethnicity, height, weight, income, education level, marital status, number of total household members, and the number of children under 18 years of age living in the home. Women will be encouraged to provide an accurate weight and if possible obtain a current weight if they have not been weighed in the past two to three weeks of filling out the survey. A scale will be provided for the women who complete the study material at the Medicaid and WIC offices. The scales will be calibrated weekly by the researcher to assure accuracy.

Participants will be given the study material to complete in private at their WIC or Medicaid office, or mailed to them by the researcher after thorough explanation of the study and verbal permission by phone. Each packet will contain a letter thanking them for completing the study material. The letter will also ask the participants to answer all questions to the best of their knowledge and thorough directions for completing and returning the packet. The packets that are mailed to participants will contain a prepaid envelope with the post office (P.O) box address stamped on it to mail the completed study material to the researcher for review. All envelops will be mailed to the pre- addressed P.O. box and the researcher will collect them frequently throughout the weeks of the data collection. All completed study material will be kept in the researcher’s office where they will be kept in a locked filing cabinet that is accessibly only to the researcher.

Data Analyses Procedures

Data will be analyzed using parametric and non-parametric statistics to analyze the study variables. Non-parametric measures include: mean, median, range, standard deviation, percentage, and frequency. The most appropriate parametric measurements for this study are: Pearson’s r correlation to test the relationships between two variables. Data entry and interpretation will be done by the Wright State University Statistical Consultation Center in consultation with the researcher and faculty advisor in the College of Nursing and Health. References

Ahn, S., Huber, C., Smith, M. L., Ory, M. G., & Phillips, C. D. (2011). Predictors of body mass index among low-income community-dwelling olderadults. Journal of Health Care for the Poor and Underserved, 22, 1190-1204. Retrieved from http://journals.ohiolink.edu.ezproxy.libraries.wright.edu:2048/ejc/pdf.cgi/Ahn_SangNam.pdf? issn=15486869&issue=v22i0004&article=1190_pobmialcoa

Bove, C. F., Olson, C. M. ( 2006). Obesity in low-income rural women: Qualitative insights about physical activity and eating patterns. Women and Health, 44(1), 57-78. doi: 10.1300/J013v44n01_04

Cleland, V. J., Ball, K., Salmon, J., Timperio, A. F., & Crawford, D. A. (2010). Personal, social and environmental correlates of resilience to physical inactivity among women from socio economically disadvantaged backgrounds. Health Education Research, 25, 268-281, doi: 10.1093/her/cyn054

Cohen, D.A., Sturm, R., Lara, M., Gilbert, M., & Gee, S. (2010). Discretionary calorie intake a priority for obesity prevention: results of rapid participatory approaches in low-income US communities. Journal of Public Health, 32, 379-376, doi: 10.1093/pubmed/fdp117

Dammann, K. W., & Smith, C. (2011). Food-related environmental, behavioral, and personal factors associated with bady mass index amoung urban, low-income African American, American Indian, and Caucasian women. American Journal of Health Promotion, 25(6), 1e-10e. doi: 10.4278/ajhp.091222-quan-397

Eicher-Miller, H. A., Mason, A. C., About, A. R., McCabe, G. P., & Boushey, C. J. (2009). The effect of food stamp nutrition on the food insecurity of low-income women participants. Journal of Nutrition Education and Behavior, 41, 161-168, doi: 10.1016/j.jneb.2008.06.004

Flegal, M. K., Carroll, M.D., Ogden, C.L., & Curtin, L.R. (2010). Prevalence and trends in obesity among US adults, 1999-2008. Journal of American Medical Association, 303, 235-241, doi:10.1001/jama.2009.2014

Ford, E. S., Zhao, G., & Tsai, J. (2011). Trends in obesity and abdominal obesity among adults in the United States from 1999-2008. Internal Journal of Obesity, 35, 736-743. doi:10.1038/ijo.2010.186

Ford, P. B. & Dzewaltowski, D. A. (2011). Neighborhood deprivation, supermarket availability, and BMI in low-income women: A multilevel analysis. Journal of Community Health, 36, 785-796. doi: 10.1007/s10900-011-9377-3

Ivers, L.C. & Cullen, K.A. (2011). Food insecurity: special considerations for women. American journal of Clinical Nutrition, 94, 1740S-1744S, doi: 10.3945/ajcn.111.012617

Jilcott, S.B., Wall-Basset, E. D., Burke, S. C., & Moore, J. B. (2011). Associations between food insecurity, supplemental nutrition assistance program (SNAP) benefits, and body mass index among adult females. Journal of American Dietetic Association, 111, 1741-1745. doi: 10.1016/j.jada.2011.08.004

Jordan, K. C., Freeland-Graves, J. H., Klohe-Lehman, D. M., Cai, G., Voruganti V. S., Proffit, J. M., Nuss, H. J., Milani, T.J., & Bohman, T.M. (2008). A nutrition and physical activity intervention promotes weight loss and enhances diet attitudes in low-income mothers of young children.Nutrition Research, 28, 13-20, doi: 10.1016/j.nutres.2007.11.005

Miles, R. & Panton, L. (2006). The influence of the perceived quality of community environments on low-income women’s efforts to walk more.Journal of Community Health, 31, 376-392, doi: 10.1007/s10900-006-9021-9 Montgomery County (2008). Health Care Safety Net Task Force Report. Retrieved from http://www.mcohio.org/Montgomery/home/docs/SafetyNetTaskForceReport_Website.pdf

Ogden, C.L., Lamb, M.M., Carroll, M.D., & Flegal, M. K. (2010). Obesity and socioeconomic status in adults: United States, 2005-2008. Centers for Disease Control and Prevention. Retrieved from http://www.cdc.gov/

Ohio Department of jobs and Family Services (2008). Montgomery County. Retrieved from http://jfs.ohio.gov/county/cntypro/pdf07/Montgomery.pdf

Polit, D.E., & Beck, C.T. (2012). Nursing research: Generating and assessing evidence for nursing practice (9th ed.). Wolters Kluwer: Lippincott Williams & Wilkins.

Townsend, M. S., Peerson, J., Love, B., Achterberg, C., & Murphy, S. P. (2001). Food insecurity is positively related to overweight in women. The Journal of Nutrition,131, 1738-1745. Retrieved from http://jn.nutrition.org/content/131/6/1738.full.pdf+html Appendix A

Potential Funding Sources

The following small grants are interested in the following; what are the contributing factors to obesity in low income adult women?

The National Institute of Nursing Research Number of Current Total Award Awards Award Level Level NIH Small Grant Program Up to two Purpose: To support small research projects $25,000 $50,000 a that can be carried out in a short period of Varies modules or up year. Max of time with limited resources. to $50,000 a two years. year http://grants.nih.gov/grants/funding/r03.htm

Total NINR Grant $100,000

Sigma Theta Tau Number of Current Total Award Awards Award Level Level International Small Grant

Purpose: To encourage nurses to contribute to the advancement of nursing through research. 10-15 Up to $5,000 $5,000 annually Due: 1 December 2012 http://www.nursingsociety.org/Research/Smal lGrants/Pages/small_grants.aspx

Zeta Phi Chapter Awards and Grants

Purpose: To fund research and WSU CONH Honors Students’ projects.

Due: Any Time 1 Up to $2,000 $2,000

Funding dates: On the 15th of the following months. March, June, September, December. http://www.wright.edu/nursing/zeta_phi/zeta_ phi_awards.html

Total Sigma Theta Tau Grants $7,000 Appendix B

Literature Review Grid

Townsend, M. S., Peerson, J., Love, B., Achterberg, C., & Murphy, S. P. (2001). Food insecurity is positively related to overweight in women. The Journal of Nutrition,131, 1738-1745. Retrieved from http://jn.nutrition.org/content/131/6/1738.full.pdf+html Problem Purpose or Research Theoretical/conceptual Research Setting, Results or Limitations of statement Specific aims Question or framework Tradition; Population Findings (include the study (stated Hypothesis and Research Type (sample), descriptive and by author(s) and Although The Key concepts Conceptual framework Sampling Plan, inferential Recommendatio individuals with purpose of the or variables was theory informed Quantitative Inclusion/exclusi statistics) ns for further poor food current study under and is stated as on criteria, study security might was to examine investigation conceptual framework of Informed Food insecurity be expected to the relationship food insecurity and its consent, Data was related to Because of the have reduced between food Examination of relation to overweight. collection overweight cross-sectional food intake, and insecurity and the over weight/ SES, socioeconomic procedures, status for women design, any thus reduced overweight as food insecurity status; BMI, body mass Instruments (P<0.0001, n = inferences body fat and measured by relationship index. used to measure 4509), but no regarding less likelihood of body mass index among the data, and Data relationship was cause and effect being (BMI) using data general analysis observed for men must be made overweight, from the population, the (P = 0.44, n = with caution and these nationally low income The Continuing 4970). should be associations representative population, and Survey of Food Of the 966 considered have not been 1994–1996 among food Intakes by women (915 preliminary. Use adequately Continuing stamp Individuals (CSFII) weighted) of secondary data studied. Survey of Food recipients. employed a reporting mild food presented certain Intakes by Independent stratified insecurity, 41% difficulties. Individuals variable is food multistage were overweight Analyses were (CSFII). insecurity. probability design compared with limited to the Dependent to obtain 34% of the food- topics, wording variable is body representative secure population of questions and mass index. samples of U.S. (P. 0.05). The variables in the Other households. The moderate food survey instrument. independent surveys consist of insecurity Validation studies variables are partial probability category of of all CSFII items income, samples of 86 women at 52% have not been occupation, and households in the overweight was reported, dietary intake. 48 contiguous significantly making states. different from the interpretation of Institutionalized food secure. Food some results and homeless security was problematic. The persons were not related to income homeless, who included. Data with a dose- were more likely from the 1994, response effect for to be food 1995 and 1996 three categories. insecure, were not CSFII were The food secure sampled. combined for this had a higher Another concern study, to yield a income than the is that food- sufficient sample mildly and insecure women of moderately may be fearful of women who self- Insecure groups answering identified as food (P , 0.0001). honestly because insecure. A final Furthermore, the honest responses sample was mildly insecure might be generated to meet had a higher perceived as the following income than the justification for criteria: >20 y old, moderately removal of reported height insecure (P children from their and weight , 0.0001). The care. Last, it is available, income prevalence of feasible that the data available, overweight was food nonpregnant and highest for those insecurity/overwei nonlactating. in the ght relationship The final sample lowest income could included 4537 category (43.8%), be attributable women and 5004 with an entirely, or in part, men. educational level to variables not in Differences of #11th grade the among food- (49.8%), who ate model, such as insecurity a diet $38.1% in psychosocial categories fat energy factors. with respect to (38.3%), who Given that the overweight rarely/never rates of both prevalence and exercised obesity and food mean incomes vigorously (41.2%) insecurity are on were examined and who watched the rise, this is an with ANOVA and television .4 h/d important topic for Tukey’s test for (46.3%). further pairwise investigation. The differences using finding that food a significance insecurity had level of P<0.05. unexpected and parsimonious paradoxical models were consequences in sought using the this study, i.e., General Linear higher rates of Model procedure overweight, and in SAS (Statistical consequently, the Analysis System) potential for to determine increased which variables incidence of best predicts obesity-related overweight. The chronic diseases, level of must be significance was addressed. 0.05 based on type III sum of squares. Further analysis was conducted with a logistic regression model to predict the probability of being overweight, the level of significance was 0.05. Bove, C. F. & Olson, C. M. ( 2006). Obesity in low-income rural women: Qualitative insights about physical activity and eating patterns. Women and

Health, 44(1), 57-78. doi :10.1300/J013v44n01_04

Problem Purpose or Research Theoretical/conceptual Research Setting, Population Results or Limitations of the statement Specific aims Question or framework Tradition; (sample), Sampling Findings study (stated by Hypothesis Research Plan, (include author(s) and Researchers This and Key The research was Type Inclusion/exclusion descriptive and Recommendations have sought to investigation concepts or guided by an criteria, Informed inferential for further study identify factors sought to variables interpretivist Qualitative consent, Data statistics) that may understand under perspective, which collection procedures, Our findings were explain the overweight and investigation acknowledges the Instruments used to 43% of the limited by the association obesity from complexity and measure data, and informants were characteristics of between food the perspective Key concepts importance of everyday Data analysis without the women we insecurity and of low-income were Body contexts in human transportation. studied. Nearly all elevated weight mothers living weight, obesity, behaviors and uses Informants were Lack of public of our informants in low-income in rural New poverty, qualitative research recruited by staff transportation were white women, women. York State, physical activity, methods, which are of programs already and high gas precluding focusing in eating patterns, useful in health research serving low-income prices also extension of our particular on food insecurity, for understanding families in these limited physical findings about body challenges to rural health, complex issues that counties: Cooperative activity. image to women of maintaining a women’s health, have been poorly Extension, the Special Transportation other racial healthy weight and understood by survey Supplemental Nutrition difficulties were backgrounds. that may be transportation. questions alone. Program for Women, twice as Similarly, our unique to rural Research Infants, and Children common among research was poverty. questions were (WIC), and Even Start (a informants who conducted in a rural addressed to family literacy program). were overweight region of the physical activity, To be eligible to or obese (53%) northeastern U.S. transportation participate, each compared and its findings may barriers, informant had to meet with those who not be physical the following criteria: be were normal generalizable to environment, a mother who was at weight or other geographic eating patterns, least 18-years-old, have underweight areas of the U.S. food insecurity, at least one child 12- (27%). Walking Multidisciplinary emotional years-old or younger was difficult in approaches are eating, body living in her home, and these settings, needed to address satisfaction, have an annual especially for obesity in low weight loss household income of informants with income rural intentions, and less than 200% of the young children women, with perceived federal poverty level. and strollers attention given to dietary Twenty-eight informants or for those with underlying deprivation. participated in this study. health problems factors such as In depth personal inhibiting transportation interviews were mobility. The difficulties, physical conducted with each food-security inactivity, informant on three status of many social isolation, occasions roughly a year informants food insecurity, apart. Informants gave (40%) changed emotional eating, written informed consent across the study and disordered upon enrollment. period. Two- eating. Upon completion of each thirds of interview, informants informants’ received a $20 gift households certificate to a local were food grocery store. Open and insecure at one closed ended questions or more were asked and the interviews. interviews lasted form on Many and a half to three hours informants and were audio taped. (60%)–food Qualitative data were secure and food analyzed using the insecure constant comparative alike–reported method, with data eating more collection and analysis food than usual occurring in response to simultaneously. Scoring stress, sadness, of informants’ responses boredom, or to the U.S. Household loneliness. Food Security Emotional Survey followed U.S. eating was Department of described by Agriculture guidelines. three quarters of informants who were overweight or obese, compared with fewer than one half (44%) of those with normal weights. Most of the participants who were overweight did see their weight as a problem. Jordan, K. C., Freeland-Graves, J. H., Klohe-Lehman, D. M., Cai, G., Voruganti V. S., Proffit, J. M., Nuss, H. J., Milani, T. J., & Bohman, T.M. (2008). A

nutrition and physical activity intervention promotes weight loss and enhances diet attitudes in low-income mothers of young children.

Nutrition Research, 28, 13-20, doi 10.1016/j.nutres.2007.11.005 Problem Purpose or Research Question or Theo Research Tradition; Settin Results or Findings Limitations of statement Specific aims Hypothesis and Key retic Research Type g, (include descriptive and the study (stated concepts or variables al/co Popula inferential statistics) by author(s) and Effective The purpose of under investigation ncep Quantitative tion Recommendatio interventions this study was tual (sampl Initially, the mean body ns for further targeted toward to evaluate a Is a nutrition and fram e), weight for responders, study low-income nutrition and physical activity ewor Sampli nonresponders, and women are physical program going to k ng comparison mothers was Limitations of this needed to activity reduce body weight and Plan, 91.9, 92.1, and 90.4 kg, with study include its combat the program for improve nutrition No Inclusi similarities in body fat (43%) high attrition and rising reducing attitudes in mothers frame on/exc and waist circumference short treatment prevalence body weight with young children? work lusion measures (range, 106-108 period. Yet, the of obesity and and improving Variables measured was criteria cm). As a result of the 8- attrition rate for diabetes in the nutrition were weight in state , week program, responders this program US. attitudes in kilograms, body fat d. Inform significantly decreased (56%) is within the mothers of percentage, and waist ed weight (x = −4.7 kg; median, range of 23% to young circumference in conse −8.8 kg; P < .001), body fat 80% experienced children. centimeters. nt, (x = −1.8%; P < .001), and in Data waist other studies collect circumference (x = −4.9 cm; recruiting ion P < .001) to a greater extent minorities. Factors proced than nonresponders (weight influencing ures, [x = −0.5 kg; median = −1.4 attrition in this Instru kg; P < .05], body fat [x = program included ments −0.5%], and waist illness of a child, used circumference [x = −2.0 cm; lack of childcare, to P < .05]). For the overall transportation measu intervention sample, the difficulties, job re declines in body weight (x = conflicts, financial data, −2.7 kg; median = −2.4 kg; P constraints, family and < .001), body fat (x = −1.2%; responsibilities, Data P < .001), and waist insufficient time, analys circumference (x = −3.5 cm; lack of family is P < .001) were highly support, personal significant. Ninety-eight stress, and Mother participants (86%) lost respondent s of weight; 1 person (1%) burden of the young maintained the same weight; questionnaires. childre 15 individuals (13%) gained Few studies have n were weight. For intervention assessed the recruite subjects available at follow- impact of a d from up (week 24), the declines in nutrition and Special body weight (x = −2.7 kg; P < physical activity Supple .001), percentage of body fat intervention on mental (−0.8%; P < .01), and waist weight loss while Nutritio circumference (−12.1 cm; P examining n <.001) remained significantly nutrition attitudes Progra lower than baseline. A in a population of m for greater low-income Wome consumption of dairy foods mothers. n, was negatively related to Therefore more Infants, perceived barriers (r = −0.22; studies should be and P < .05). Mothers who done to support Childre increased their dairy servings the need for n reported less confusion public health (WIC) regarding nutrition (r = −0.28; clinics to consider clinics, P <.01) and fewer complaints adopting weight commu of the effort required to eat management nity healthful foods (r = −0.26; P programs for their centers < .01). Subjects who clients. , and decreased their cholesterol church intake by post intervention es. reported less difficulty in Eligibili changing their dietary habits ty (r = 0.24; P < .01). Overall, criteria the weight loss intervention for was rated highly. More than both 90% of participants reported groups learning a great deal from include the program. In particular, d women stated that the in- African class exercise (88.3%), Americ weekly weigh-ins (85.3%) an, and wearing a pedometer white, (84.7%) were very useful or components. Hispani c ethnicit y; younge st child of 1 to 4 years; BMI of at least 25 kg/m2; low- income (qualifi cation for WIC or food stamps or annual househ old income >200% of the federal poverty index); and absenc e of breastfeeding (>5 min/d). The final interve ntion sample size was 114 of 260 who came to the first class, for an attrition rate of 56%. 33 overwe ight/ob ese compar ison mother s of similar demog raphic backgr ound provide d anthro pometri c data at weeks 0 and 8. Height was determi ned with a stadio meter , and weight was measur ed with an electro nic weighi ng scale. Body mass index was calcula ted as kilogra m per square meter. Percen tage of body fat was assess ed via bioimp edance with a body compo sition analyz er. Waist circumf erence was obtaine d by positio ning a measur ing tape around the abdom en at the highest lateral border of the right iliac crest, as recom mende d by NHAN ES III. Interve ntion mother s reporte d a 24- hour diet recall and 2 days of food records at weeks 0 and 8, and a 24- hour recall weekly during each class. The Nutritio n Attitud es Scale consist ed of 21 items with 4 subsca les— sensor y motivat ors, emotio nal eating, perceiv ed barrier s, and healthf ul eating. The SPSS softwar e (versio n 11.5, 2003, SPSS Inc, Chicag o, IL) was used to analyz e data. Statisti cal signific ance was shown only if the probabi lity (P) values were less than . 05.

Cleland, V. J., Ball, K., Salmon, J., Timperio, A. F., & Crawford, D. A. (2010), Personal, social and environmental correlates of resilience to physical

inactivity among women from socio-economically disadvantaged backgrounds. Health Education Research, 25, 268-281,

doi: 10.1093/her/cyn054 Problem Purpose or Research Theoretical/ Research Setting, Population Results or Findings Limitations of the statement Specific aims Question or conceptual Tradition; (sample), Sampling (include descriptive study (stated by Hypothesis and framework Research Plan, Inclusion/ and inferential author(s) and Although the This study Key concepts Type exclusion criteria, statistics) Recommendations benefits of aimed to or variables No Informed consent, Data for further study physical activity examine under framework Quantitative collection procedures, Medium and high levels are well correlates of investigation was stated. Instruments used to of self-efficacy for The potential documented, a achieving measure data, and Data walking (85 and 213% limitations include considerable recommended What are the analysis greater prevalence, the cross-sectional proportion of levels of factors that respectively), high self- nature of the study the population physical correlate to Using a stratified efficacy for vigorous and the relatively is inactive, activity among resilience to sampling procedure, physical activity (59% small sample size, failing to meet women of low physical participants were greater prevalence) and the use of self- guidelines socio- inactivity? The recruited from 45 medium and high report measures which economic variables were neighborhoods of enjoyment of walking (although valid and recommend position. personal, social, different socio-economic (68 and 139% greater reliable measures accumulating and strata (low, mid and high) prevalence, were used where 30 min day_1 environmental in Melbourne, Australia. A respectively) were possible), the study of moderate- factors. Twenty- total of 2400 women were associated with was limited to one intensity six personal, selected, with 975 from achieving recommended geographical area physical activity social and low, 780 from mid and LTPA (Table III). High and the use of one on most days environmental 645 from high socio- barriers (59% lower indicator of SEP. of the week. factors were economic position (SEP) prevalence), medium Non-leisure assessed. The neighborhoods. A second and high intentions (94 physical activity key concept in independent sample of and 282% greater was not examined this study was 2400 women from the prevalence, in this study, resilience. same neighborhoods respectively), having a although our was drawn in the same set physical activity previous work using manner to complete routine (158% greater data from this same a separate nutrition prevalence) and fitting study suggests that survey, with respondents physical activity around women of low SEP to that survey being schedules (57% greater do not engage in asked to complete the prevalence) were also more transportation physical activity survey. associated with and work-related Leisure time physical achieving recommended physical activity activity (LTPA) was LTPA. For social factors, than women of high assessed using the high friend/colleague SEP. Further International Physical social support (44% research examining Activity Questionnaire. greater prevalence), with the effectiveness of The study was approved medium and high levels interventions that by the Deakin University of social participation include strategies Human Research Ethics (44 and 67% greater promoting self- Committee. A physical prevalence, efficacy for walking, activity survey was respectively) and with enjoyment of posted by mail to 2400 sport/recreation club walking, intentions women and nutrition membership (50% to be active and surveys to a separate greater prevalence), was developing set sample of 2400 women. associated with routines for physical In all, 1045 women recommended LTPA. activity in women of responded to the initial Having busy roads to low SEP is physical activity survey cross when warranted. Doing so (44% response rate), and walking was the only with careful of the women completing environmental factor consideration to the the nutrition survey (n = associated with broader 1136; 47% response achieving recommended socioeconomic, rate), 509 (45% of LTPA (36% greater environmental and nutrition survey prevalence). In political context respondents; 21% of multivariable analyses, may be an example those initially approached the prevalence of of how future to complete the nutrition achieving LTPA was research has the survey) also completed approximately twice that potential to the physical activity in those with high self- integrate resilience survey. In the final model, efficacy for walking, high theory and social– personal, social and intentions to be active ecological physical environmental and a set routine for frameworks in order factors that were physical activity to better understand significantly associated compared with those and promote with LTPA (P < 0.05) with low self-efficacy physical activity were selected for entry for walking, low behaviors among into a multivariable intentions to be active women of low SEP. model. Chi-squared tests and no set routine for (categorical data) and physical activity, one-way analysis of respectively. variance (continuous data) were used to determine whether covariates differed significantly across LTPA categories. In the final model, personal, social and physical environmental factors that were significantly associated with LTPA (P < 0.05) were selected for entry into a multivariable model. All analyses were conducted using Stata Version 9.2.

Ahn, S., Huber, C., Smith, M. L., Ory, M. G., & Phillips, C. D. (2011). Predictors of body mass index among low-income community-dwelling older adults. Journal of Health Care for the Poor and Underserved, 22, 1190-1204. Retrieved from

http://journals.ohiolink.edu.ezproxy.libraries.wright.edu:2048/ejc/pdf.cgi/Ahn_SangNam.pdf?issn=15486869&issue=v22i0004&article=1190_pobmialcoa

Problem Purpose or Research Theoretical/concept Research Setting, Results or Limitations of statement Specific aims Question or ual framework Tradition; Population Findings the study (stated Hypothesis Research Type (sample), (include by author(s) and With the This study and Key No framework was Sampling Plan, descriptive and Recommendatio increasing investigated concepts or stated. Quantitative Inclusion/ inferential ns for further number of older demographic, variables exclusion statistics) study adults, escalating behavioral, and under criteria, obesity rates in functional investigation Informed Three-fourths of This study has this population predictors of consent, Data participants were limitations that will not only overweight and The present collection female, and two- should be affect individual obesity, using study: (1) procedures, thirds of the considered. First, health and well- secondary data assesses body Instruments participants were these results being, but it will from 705 mass index used to measure age 75 years or were based on also challenge community- (BMI) data, and Data older. More than cross-sectional health care dwelling values among analysis 40% of the data, which limits delivery and individuals low-income participants our ability to financing aged 65 years older adults Data were reported determine systems in and older living in the collected in 2006 engaging in no causality. America. receiving or community; (2) from 1,228 physical activity. Second, all seeking Medicaid identifies community A total of 78% of variables in this personal care predictors of dwelling adults our participants study were self- services. obesity and who were were either obese reported, which overweight in receiving or (50%) or may have led us this population; applying for overweight to underestimate (3) investigates Medicaid (28%). Bivariate BMI (although a the personal care relationships recent study development services (PCS) in indicate, reported and promotion Texas. Study proportionally significant of programs participants were more obese agreement designed to recruited in two participants were between self- improve the ways. Those between the ages reported BMI and nutritional already receiving of 65 and 74 measured BMI status and Medicaid PCS years, were values among quality of were assessed female, had lower older adults [i.e., life of when the annual cognitive 79% of men and community- functional performance 77% of dwelling older assessment scale scores, and women]).72 Third, adults, required by had greater pain although especially Medicaid took scores. In the estimating the those with low place. Other initial model, the socioeconomic incomes who participants were results status involved in seek services assessed when indicated that the current study, through public they attempted to obesity was financial programs. access the observed more tradeoffs, and Dependant Medicaid among those who speaking Spanish variables were personal care were female (OR were inherently weight and services program = 1.95; P <.001), limited proxy height. during the study whereas obesity measures Independent period specified was observed representing variables were for data less among those income and age, sex, collection. this who aged 75 ethnicity. economic study focuses on years and older status, primary the 705 Texas (OR = 0.33; p language, participants who <.001), had better lifestyle were cognitive function behaviors, disadvantaged in (OR = 0.75; p pain, and terms of being =.006), or were physical poor and having smokers (OR = activity. functional 0.37; p disability. To be =.012). Being included in this overweight was study, less frequently participants must observed among have reported those aged 75 being aged 65 or years and older older, having a (OR = 0.57; p body mass index =.038). In the final (BMI) equal to or model, obesity greater than 18.5 was more kg/m2, and common among speaking English those who were or Spanish as female (OR = their primary 2.02; p <.001), language. whereas obesity State Medicaid was less common caseworkers among those who were trained to aged 75 years use an and older (OR assessment tool =0.31; p <.001), that contained a had better subset of items cognitive function found on the (OR Community =0.77; p =.003), Health and smoked Assessment cigarettes (OR (RAICHA = 0.36; p =.009). ©) that is itself a In addition, subset of items in this final model, from the Minimum those aged 75 Data Set for years or older Home Care (MDS were less likely to HC©). All three be overweight pain items were (OR = 0.54; p summed into a =.016). The final single scale model in this (Cronbach’s analysis shows alpha = 0.87). that those who Cognitive function were female (OR was assessed = 2.54; p =.001) using the and had greater cognitive pain performance (OR =1.07; p scale. =.033) were more Participant’s likely to be obese. functional Conversely, those limitations were who aged 75 assessed using years and older items related to (OR=0.62; p activities of daily =.022) and had living (ADL) and better cognitive instrumental function (OR = activities of daily 0.85; p = .008) living (IADL). A were less likely to principal be obese. component Smoking became analysis was non-significant in performed to this analysis. generate ADL Being obese and IADL scales. compared with ADL item scores being overweight were summed was associated into a single scale with being (Cronbach’s younger, being alpha  0.87). female, and Stata Version 10 having better was used for all cognitive function. analyses. Being female increases the odds of being obese relative to having a normal weight or being overweight. Miles, R. & Panton, L. (2006). The influence of the perceived quality of community environments on low-income women’s efforts to walk more.

Journal of Community Health, 31, 376-392, doi: 10.1007/s10900-006-9021-9

Problem Purpose or Research Theoretical/concept Research Setting, Results or Limitations of statement Specific aims Question or ual framework Tradition; Population Findings the study (stated Hypothesis and Research Type (sample), (include by author(s) and Although rates The purpose of Key concepts No framework was Sampling Plan, descriptive and Recommendatio of obesity are the present or variables stated Quantitative and Inclusion/ inferential ns for further increasing study is to under Qualitative exclusion statistics) study across all assess whether investigation Pilot Study. criteria, demographic low-income Informed The women who The findings of and social women What are the consent, Data completed the this pilot study are groups, participating in factors that collection study had only suggestive differences in an intervention support and procedures, significantly more given its small the prevalence designed to constrain low- Instruments health problems size and the fact of obesity, increase their income women used to measure (5 ± 3 diseases) that no objective related chronic physical to walk more? data, and Data (p < 0.05) than measures of diseases and activity were Increasing the analysis the women who participants’ associated risk able to do so number of steps dropped out (3 ± residential factors by social and to gain a day will show Overweight and 2 diseases). environments class remain health benefits, health benefits in obese women on There were no were available. significant, and to the participants. Medicaid differences particularly investigate Dependant between the ages between the among women. what difference variable is body of compliers and the perceived weight and body 30 to 65 years of non-compliers on community mass index. The age were education, environment independent recruited for the number of made in variables are study. 46 medications, and supporting age, education, potential subjects number of or constraining medications, and agreed to diseases that the their efforts diseases. participate in the women had. study. Subjects There was a were excluded trend (p=0.07) for from the study if the non-compliers they were to be older than currently the compliers. participating in an Compliers exercise program, increased from an if they could not average of 6,306 walk, if they had a to 10,870 body mass index steps/day. Non- (BMI) less than compliers on the 25 kg/m2 and/or if other hand did they were not on not increase their Medicaid. steps (4,929 to Total sample was 4,742 steps/day). n Compliers = 29. Approval of experienced the study was significant obtained from the improvements in University the Institutional measurements of Review Board. body weight and Baseline BMI. No measurements improvements were taken on all were observed for participants. the women who Measurements did not increase included resting their steps over blood pressure the 12-month and heart rate, period. The 6- anthropometric month, 9-month measurements of and 12-month height, body BMI values were weight, and hip significantly lower and waist than baseline and circumferences; 3-month values fasting blood for the women samples were who increased analyzed for their number of hemoglobin, steps. The hematocrit, findings of the in- glycosylated depth interviews hemoglobin A1C, indicate that most total cholesterol, of the increased high density walking took lipoproteins, place in triglycerides, neighborhoods. fibrinogen, and All of those who high sensitivity C- increased their reactive protein. steps by more Every three than 10,000 (n = months the 5) as well as two women were who didn’t but reevaluated on all were already the above taking 7,000 to measurements. 9,000 steps per Subjects were day, reported paid $125.00 to primarily walking participate in the in their study; they were neighborhoods. given $10.00 for Those who each visit at increased their baseline, three- steps by at least month, six-month 2,000 per day (n and nine-month = 10) reported and at the last that they did most visit (12-month) of their walking the subjects were either in their given $85.00 for neighborhood or their participation at the mall. Of the in the study participants who regardless of reported that they whether or not had places to they increased walk to near their steps. Of the home (n = 8), 38 29 participants percent (n = 3) who completed succeeded in the study, 25 increasing their agreed to be steps by at least interviewed. The 2,000 per day interview protocol compared to only included open- 22 percent (n = 2) ended questions of those who about the place reported no where destinations near respondents home spent their (n = 8). Three growing-up years compliers and and the extent to five non- which they compliers did not walked to know whether different places, there were places rode a bike, or to walk to in their played sports. neighborhood. Safety and security concerns were mentioned exclusively by non-compliers (n = 5) in response to an open-ended question about the constraints they faced in trying to increase their steps. Responses to other questions in the interview indicated chronic health problems and stress made it more challenging for many women to increase their physical activity. Ford, P. B. & Dzewaltowski, D. A. (2011). Neighborhood deprivation, supermarket availability, and BMI in low-income women: A multilevel analysis.

Journal of Community Health, 36, 785-796. doi: 10.1007/s10900-011-9377-3

Problem Purpose or Research Theoretical/ Research Setting, Population Results or Findings Limitations of statement Specific aims Question or conceptual Tradition; (sample), Sampling (include descriptive and the study Hypothesis and framework Research Plan, Inclusion/ inferential statistics) (stated by There is a To determine Key concepts Type exclusion criteria, author(s) and growing whether the or variables No Informed consent, Rural WIC cases had a Recommendati consensus that association under framework Quantitative Data collection mean pre-pregnancy BMI ons for further recent dramatic between investigation was stated. procedures, of 27.36 (±7.28), which study increases neighborhood Instruments used to was significantly higher in the incidence deprivation and The hypotheses measure data, and than metropolitan (26.88 ± This study only of obesity within BMI is mediated tested in this Data analysis 6.87) and micropolitan examined the the US are by the study include: (1) WIC cases (26.85 ± 6.61). association of unlikely availability of Tract deprivation The dataset used in this The percentage of WIC deprivation, due to retail food is associated study included all mothers who resided in supermarket psychosocial stores, and with increased Kansas mothers enrolled high deprivation tracts availability, and and biological whether this BMI, in the Special varied widely across the BMI among low- changes at the relationship independent of Supplemental Nutrition urban–rural continuum, income individual varied across individual level Program for Women, with the highest participants in level, but the urban rural covariates. Infants, and Children percentage of WIC the WIC instead are continuum. (2) The (WIC) between October mothers residing in high program in associated with association 10, 2004 and December deprivation tracts in Kansas. we changes in between tract 31, 2006. Pregnant, metropolitan areas relied on a social, and BMI varies breastfeeding, or (64.96%), as compared to statewide, economic, and along postpartum mothers with metropolitan areas historical built the urban–rural family incomes of (59.30%) and rural areas database of food environments continuum, with <185% of the federally (39.39%). Micropolitan stores available that encourage a stronger designated poverty level areas also had the lowest in 2005. While an association for family size are percentage of WIC previous studies imbalance in more eligible for enrollment in mothers residing in low report high between caloric urbanized areas. the WIC Program. All deprivation tracts (8.10%) reliability of intake and (3) The information in the WIC as compared to rural these expenditure association dataset was recorded at (8.69%) and metropolitan databases, among between tract the initial certification (18.05%) areas. The studies individuals. deprivation and and subsequent WIC association between tract employing BMI is mediated Clinic visits, and deprivation and BMI varied ground-truthing by the number of collected by KDHE as by urban influence. Within in rural areas supermarkets part of the Pregnancy our metropolitan sample, suggest some within a census Nutrition Surveillance deprivation was linearly misclassification tract. Variables System (PNSS). Pre- associated with BMI with a of stores. in the PNSS partum BMI (calculated 0.524 unit increase in BMI Additionally, used in this with self-reported pre- associated with we did not study include: pregnancy weight) and intermediate deprivation, characterize mother’s age at postpartum BMI and a 0.840 unit increase stores by quality, certification, (objectively measured at associated with residence and some parity, race, first post-partum in a high deprivation tract studies ethnicity, years visit) were highly as compared to residence have found of schooling, and correlated (Cronbach’s in a low deprivation tract. significant household α = 0.95, P < 0.001). There was no association differences in monthly income. The final sample between tract deprivation the quality of Dependant included 21,166 unique and BMI among WIC stores by tract variable was cases. Urban Influence women in rural areas. deprivation. body mass Codes (UIC) for all Among WIC mothers who index. counties in Kansas lived in metropolitan areas, were obtained from women who lived in USDA-Economic intermediate and high Research Service 2003 deprivation tracts had a Urban Influence Code 0.622 and 0.937 unit dataset. Census tracts increase in BMI, serve as the proxy for respectively, after neighborhoods in this controlling for individual study. Socioeconomic demographic data at the census tract characteristics, as level were extracted compared to women who from US 2000 Census lived in low deprivation SF-3 files, and used to tracts. Tract deprivation calculate tract was associated with deprivation. Tract increased BMI among low- deprivation scores were income women in our calculated using study. maximum likelihood factor analysis with a varimax rotation to maximize score loadings. One factor was identified (Eigenvalue = 4.83; Cronbach’s a = 0.85) that captured a cumulative 60.83% of variance. Data on food stores were obtained from the Kansas Department of Agriculture retail food establishment licensure list for 2005. All data were reduced and statistical analyses were run in SPSS (v. 15.0, SPSS Inc, Chicago, IL). Jilcott, S.B., Wall-Basset, E. D., Burke, S. C., & Moore, J. B. (2011). Associations between food insecurity, supplemental nutrition assistance program (SNAP)

benefits, and body mass index among adult females. Journal of American Dietetic Association, 111, 1741-1745. doi: 10.1016/j.jada.2011.08.004 Problem Purpose or Research Theoretical/ Research Setting, Population Results or Findings Limitations of statement Specific aims Question or conceptual Tradition; (sample), Sampling Plan, (include descriptive the study Hypothesis and framework Research Inclusion/ exclusion and inferential (stated by Obesity is a This study’s Key concepts Type criteria, Informed consent, statistics) author(s) and major public purpose was to or variables No Data collection Recommendati health problem examine under framework Cross procedures, Instruments Despite the fact that all ons for further disproportionate cross-sectional investigation was stated. sectional, used to measure data, and women were SNAP study ly affecting low- associations Quantitative. Data analysis participants, the income between food In the current majority of women In the future, it individuals, insecurity, study, cross- This cross-sectional study reported marginal or will be important minorities, and Supplemental sectional took place in a small urban low food security. to conduct women. Nutrition associations center located in Pitt County, Pearson’s correlation longitudinal Assistance between BMI, eastern North Carolina. coefficients between analyses to Program food security, Sample size was n=202. variables of interest examine (SNAP) SNAP dollars Two trained interviewers indicated that potential benefits per per household recruited a convenience perceived stress was moderation of, household member, and sample of SNAP participants positively associated and mediation member, perceived stress between October 2009 and with food insecurity, between, food perceived were examined April 2010 from the Pitt such that greater insecurity and stress, and among female County Department of Social perceived stress was BMI by SNAP body mass SNAP Services waiting area. associated with higher dollars per index (BMI) participants in Eligibility criteria were being food insecurity household among female eastern North female between the ages of (r=0.36, P<0.0001). As member. Future SNAP Carolina. 20 and 64 years, English- hypothesized, food researchers participants It was speaking, primary food insecurity was should examine in eastern North hypothesized shopper in the household, a positively related to the relationship Carolina that SNAP current SNAP benefit BMI (0.18; P<0.05). between stress, dollars per recipient, planning to reside Although perceived food insecurity, household in Pitt County for the stress was positively and overeating member would next year, and able to return associated with food among SNAP be inversely to the office for follow-up 1 insecurity, perceived participants. associated with week later. Informed consent stress was not Continued SNAP food insecurity was obtained. The study associated with BMI. education efforts and food was approved by the East BMI was positively should focus on insecurity would Carolina University Medical associated with food supporting be positively Center Institutional Review insecurity (parameter resource- associated with Board. Household food estimate =0.48, constrained perceived stress. insecurity was measured standard error=0.23; women in In keeping with using the validated US P=0.04), adjusted for making healthful previous Department of Agriculture age and physical selections within research 18-item core food security activity. Perceived the current findings, an survey module. SNAP stress was positively obesogenic food additional benefits per household related to food environment. hypothesis was member were measured by insecurity (parameter Other potential that food asking women how many estimate=0.9, confounders insecurity would children younger than 18 standard error=0.18; should be be positively years of age lived in their P<0.0001), when both included in associated with household, and how much SNAP benefits per future research, BMI, moderated their household received in household member including money by SNAP SNAP benefits the last time and perceived stress spent on benefits per benefits were distributed. were included in the nonfood items household Perceived stress was same model, which and duration of member. measured using the 14-item was also adjusted for SNAP Dependant Cohen’s Perceived Stress race. The mean BMI of participation.The variables were Scale, with responses given women receiving first limitation of perceived stress the appropriate values as >$150 per household this study is the and body mass outlined in Cohen and member was cross-sectional index. The colleagues. Two trained significantly lower than study design. independent research assistants weighed the mean BMI of Second, a variables were each participant twice to the women receiving convenience food insecurity nearest 0.1 lb using the <$150 per household sample of and SNAP Tanita WB- 100A Digital member (33.1 [9.1] vs SNAP benefits per Medical Scale. Height was 35.8 [9.9]; P=0.04). participants was household measured twice to the recruited and member. nearest 0.1 cm using the enrolled, limiting Seca 214 Portable Height The Rod. Potential covariates generalizability were race, age, physical of results. activity, and employment Finally, a cursory status. Race was measure of dichotomized as black or physical activity white/other. T tests were was obtained in used to examine the order to reduce differences in food insecurity respondent and BMI by the amount of burden. A more SNAP benefits per detailed household member. measure of Pearson’s correlation physical activity coefficients were may have used to examine bivariate provided for relationships between BMI, more thorough perceived stress, food control of this insecurity, and SNAP dollars potential per household member, with confounder. P values < 0.05 used to determine statistical significance.

Dammann, K. W., & Smith, C. (2011). Food-related environmental, behavioral, and personal factors associated with bady mass index amoung urban, low-income

African American, American Indian, and Caucasian women. American Journal of Health Promotion, 25(6), 1e-10e.doi: 10.4278/ajhp.091222-quan-397

Problem Purpose or Research Theoretical/ Research Setting, Population Results or Findings Limitations of statement Specific aims Question or conceptual Tradition; (sample), Sampling Plan, (include descriptive the study Hypothesis and framework Research Inclusion/ exclusion and inferential (stated by The majority of To examine Key concepts Type criteria, Informed consent, statistics) author(s) and the adult racial/ethnic or variables Social Data collection Recommendati population in the differences in under Cognitive Cross- procedures, Instruments The sample (n = 367) ons for further United States is relationships investigation Theory sectional, used to measure data, and was 49% African- study overweight or between food- community Data analysis American, 40% obese, and related No research based American Indian, and Additional certain groups environmental, questions or survey. This study took place in 12% Caucasian, with a exploration of are at higher behavioral, and hypothesis was Quantitative community sites and low- mean standard these factors risk, including personal factors noted in this income housing deviation age of 35.4 ± may help to low-income and low-income study. The main developments in the Twin 9.9 years. Eighty develop more women. women’s weight variables were Cities metropolitan area. percent of participants tailored and status using race/ethnicity Subjects included low- received food stamps, effective Social Cognitive and BMI. income African-American, and 74% reported low approaches to Theory (SCT) Nutrition American Indian, and to very low food nutrition as a framework. knowledge, self- Caucasian women ≥ 18 security. Food security education and efficacy, years of age (n = 367). was status was also interventions in emotional Inclusion criteria was each significantly low-income coping, food women had to be English associated with communities in insecurity, and speaking, ≥ 18 years of age, racial/ethnic identity (p an effort to health beliefs reside in the Twin Cities = .032). The majority improve were also metropolitan area, be a of the sample was women’s weight variables in this mother of at least one 2 – 18 overweight or obese status. The study. year old child in the (82%; BMI ≥ 25.0). inclusion of only household, and report Although mean BMIs urban, low- current use of a food were not significantly income, English assistance program. All different racial/ethnic speaking women women that were pregnant groups, racial/ethnic is one limitation or did not fit in these criteria identity was of this study; were excluded from the significantly therefore, results study. Recruitment took associated with may not be place at food stores, food categorical BMI status generalized to assistance programs, public (p = .039). All rural low-income libraries, low-income regression models women, men, housing developments, and were statistically and the non- homeless shelters by using significant, although English speaking informational flyers, verbal the personal population. Also announcements and the regression models physical activity, snowballing technique. All predicted the greatest which participants provided written proportion of the contributes to informed consent. Surveys variance in BMI for energy balance took approximately 60 – 70 African-American and weight minutes to complete. The (15% of the variance), status, was not University of Minnesota American Indian (22% measured Institutional Review Board of the variance), and approved this study. The Caucasian (37% of the USDA 18 item Household variance). Food Security Survey Module was used to evaluate food security. Weight and height were taken to calculate the women’s BMI. Analysis were conducted by using SPSS (version 17.0) with the significance set at p < .05. racial/ethnic differences were examined with the Bonferroni correction and x2 tests. Pearson correlation coefficients were used to examine the relationships between each question and the outcome variable of interest, BMI. Multiple linear regression analyses were conducted by using Enter method with the significant questions under each construct included in the model, controlling for age and homelessness. In all, nine regression models were tested, one for each SCT construct within each racial/ethnic group, to determine which construct explained the largest proportion on the variance in each group’s BMI. Eicher-Miller, H. A., Mason, A. C., About, A. R., McCabe, G. P., & Boushey, C. J. (2009). The effectof food stamp nutrition on the food insecurity of low-income

women participants. Journal of Nutrition Education and Behavior, 41, 161-168, doi: 10.1016/j.jneb.2008.06.004 Problem Purpose or Research Theoretical/ Research Setting, Population Results or Findings Limitations of statement Specific aims Question or conceptual Tradition; (sample), Sampling Plan, (include descriptive the study Hypothesis and framework Research Inclusion/ exclusion and inferential (stated by The prevalence The objective of Key concepts Type criteria, Informed consent, statistics) author(s) and of food this study was or variables Social Data collection Recommendati insecurity in to examine the under Cognitive A single- procedures, Instruments Participants numbered ons for further 10.9% of all effect of Food investigation Theory blind used to measure data, and 236 with 17 lost to study households in stamp nutrition randomized Data analysis attrition, leaving a final 2006 is education It was design. sample of 219 There were surprising (FSNE) lessons hypothesized Quantitative Participants in this study participants. The several considering the on the food that the series of were eligible experimental group limitations of this food supply insecurity and 5 tailored to receive FSNE services. comprised 137 study. A larger and wealth of food educational Criteria for Indiana FSNE participants, and the sample size may the United insufficiency in lessons provided participation include being control group 82. have allowed for States. participants through age 18 or older; qualified to Forty percent of the the detection of using a FSNE would receive food stamps or participants of this distribution randomized, improve a under 130% of the income- study were food trends for controlled participant’s to-poverty ratio; and insecure, a high independent intervention. It self-reported head of household, or the prevalence compared variables as they was food security person responsible for food with the 2005 US related to the hypothesized level and purchases and food dollar prevalence of 11.0%. change in food that the series food sufficiency management. In this study, Upon completion of 5 security or food of 5 tailored compared with participants were additionally FSNE lessons, there insufficiency. educational participants limited to females, as this were significantly more Applicability lessons receiving no represents the majority of food-sufficient of these findings provided FSNE lessons. FSNE clients. Assistants participants in the to other through from 28 Indiana counties experimental group populations may FSNE would volunteered, and 24 of these than the control group also be limited improve a assistants recruited (P =.03). Analysis of by the lack of participant’s participants. Counties were covariance modeling diversity in the self-reported composed of a for the response sample (96.8% food security representative mix of urban variable ‘‘food non- Hispanic level and and rural areas. In addition security’’ with the white, 2.3% food sufficiency to prior extensive FSNE predictor variable Hispanic, 0.5% compared with training, the participating ‘‘treatment group’’ black, and 0.5% participants FSNE assistants completed indicated that subjects other). This receiving no training on research in the experimental sample FSNE lessons. techniques such as proper group were more likely is very similar to randomization and survey to improve their food the 2004 administration. All security levels race/ethnic participants’ FSNE lessons compared with control group and food security group participants. distribution of questionnaires were Participants in the the counties completed in client homes or experimental group represented at the community locations had a significant in the sample: where the clients were overall improvement 97% non- recruited. Some of these (P = .03) in food Hispanic white, locations were county offices security, a positive 2% Hispanic, of the Special Supplemental change of 0.37 on the 0.7% black, and Nutrition Program for 6-point scale 0.3% other. Women Infants and compared to the These Children, Head Start control group. The percentages centers, and food pantries. model R2 value are similar in The Human Subjects indicates that 30.7% comparison with Committee approved all of the relationship the 2004-2005 research activities prior to between change in total race/ethnic commencement of the food security and group project, and all subjects treatment group is distribution signed a written consent explained by the of Indiana: 85% form prior to their model. Similar results non-Hispanic involvement in the study. were found for white, 4% Interventions were given by analysis of covariance Hispanic, 9% trained FSNE assistants. modeling for the black, and 2% The FSNE assistant response variable other. Past administered and recorded ‘‘food sufficiency’’ research has the pre- and post- with predictor variable shown that questionnaires in an ‘‘treatment group’’. race/ethnicity interview with the participant. Participants in the may be The food security scale was experimental group associated scored as directed by the had a significant with the USDA Guide to Measuring improvement of 0.8 relationship of Household Food Security. (P=.04) in food education to Model assumptions were sufficiency relative to food security examined using stem plots, no improvement in the change, so QQ plots, and by plotting control group. The the results may residuals against the model R2 value not apply in a predicted values. Results indicates that 43.8% of more diverse were considered the relationship sample. Further significant at P <.05, and all between change in research is statistical analyses were food security and needed to performed with SAS treatment group is address whether (Version 9.1., SAS Institute explained by the food security Inc., Cary, NC, 2003). model. improvements can be maintained over time. Appendix C

Informed Consent

Title of Study: Food insecurity and barriers to physical activity in low-income women of the Dayton area.

Agreement to Participate: This signed consent indicates my willingness to participate in this study.

Purpose of Study: The purpose of this study is to evaluate food insecurity, barriers to physical activity, and there correlation to body mass index.

Procedures: I have been asked to participate in a study by Shawn Kise RN, BSN MS student at Wright State University in Dayton, Ohio. The study will require me to complete questionnaires on food security and barriers to physical activity. The survey will take approximately 30 to 45 minutes to complete. In addition, I will be asked questions such as my age, education level, income status, ethnicity, marital status, total number of family members in the household, height, and provide an accurate weight in the demographics section. I will be asked questions on my access to healthy, nutritious, and amounts of food available to me in this survey. I will also be asked questions regarding factors that create a barrier for me to exercise. I understand that I do not have to answer any questions that I am not comfortable answering. Should I desire a summary of the data collected in this study, I may request it by writing my name and contact number at the bottom of the informed consent.

Risk/Benefits: Completing the study does not involve known physical risks of discomfort to me. If I do not feel comfortable answering any of the questions on the questionnaires, I can skip the questions without penalty or coercion. I realize that the information collected from this study will be helpful to Shawn Kise and other providers to provide a better understanding about food insecurity and the barriers to physical activity in low-income women in this moderate- sized city in the Midwest. The findings of this study will be used to develop and implement a tailored intervention to improve body mass index related to food insecurity and barriers to physical activity among women in this moderate- sized Midwestern city. I will receive a $10 VISA gift card that can be used where VISA cards are accepted after the completed study material is received.

Explanation Received: The questionnaires have been explained to me in the cover letter of the study material. The risks and benefits have also been explained to me. I understand that if I have any questions or concerns, I can use the contact information in the study material to have them answered before I complete the survey.

Confidentiality: I understand that the information about me collected in these questionnaires will be kept strictly confidential and that I will not be identified in any publication or public health agency report. Confidentiality will also be maintained in all processes of information collection and data entry into the computer system. No one other than Shawn Kise, data entry clerk, and the Statistical Consultation Center at Wright State University will have access to my completed survey. The surveys will be destroyed after completion of the study.

Right Not to Participate: I understand that by receiving this survey I am not required to be in this study and can refuse to participate.

Signature of Participant______

Date______

Signature or Principal Investigator______

Date______

I request a copy of the study report. Thank you.

Signature______Contact number______Appendix D Appendix E

Community Informational Flyer

Attention Women of the Dayton area

I invite you to be a participant in a study (questionnaire survey) conducted by Shawn Kise RN, BSN MS student at Wright State University.

The purpose of this study is to examine the influence of food security status and barriers to physical activities affect body mass index in the low-income women of the Dayton area. You will be asked to complete a demographic questionnaire and questionnaires that addresses food security and physical activity. The socio-demographic questionnaire will ask age, race/ethnicity, height, weight, income, education level, marital status, number of total household members, and the number of children under 18 years of age living in the home. All participants will be asked to provide an accurate weight and body mass index will be calculated by the researcher using your height and weight from the socio-demographic questionnaire. If you receive the study material by mail you will be asked to mail the survey to the researcher in a prepaid envelope that will be provided for you.

There are many benefits to this study. The information gained in this study will provide a better understanding about food insecurity and the barriers to physical activity in low-income women in this area. The findings of this study will be used to develop and implement a tailored intervention to improve body mass index related to food insecurity and barriers to physical activity among low- women in this area. Every woman that completes the survey and mails it in will receive a $10 VISA gift card that can be used anywhere that VISA is accepted. After completing and returning the study material you will receive a thank you card with my information to contact me about receiving your gift card.

If you participate in this study, you will be asked to sign a permission form that will explain to you the risk and benefits of the study. If there are questions on the questionnaires you’re not comfortable answering you can skip the question without penalty or coercion. The researcher will be available through e-mail or phone contact with any questions or concerns you may have about participation in this study. All information will be confidential and only the researcher, data entry clerk, and Statistical Consultation Center at Wight State University will have access to your information.

In order to participate in the study, you must be:

 female

 18 to 65 years of age

 Of low-income status

 Live in Dayton or surrounding areas

If you would like to participate in this study you can fill out an information card and receive the study packet at the office you received this flyer, or by contacting Shawn Kise by email ([email protected]) or by phone (419-512-3724). If there is anyone you know that might want to participate in the study that meet the above criteria please have them contact me by using my contact information.

Appendix F

U.S. HOUSEHOLD FOOD SECURITY SURVEY MODULE:

THREE-STAGE DESIGN, WITH SCREENERS

Economic Research Service, USDA

July 2008

Revision Notes: The food security questions are essentially unchanged from those in the original module first implemented in 1995 and described previously in this document.

July 2008:

* Wording of resource constraint in AD2 was corrected to, “…because there wasn’t enough money for food” to be consistent with the intention of the September 2006 revision. * Corrected errors in “Coding Responses” Section September 2006:

 Minor changes were introduced to standardize wording of the resource constraint in most questions to read, “…because there wasn't enough money for food.”  Question order was changed to group the child-referenced questions following the household- and adult- referenced questions. The Committee on National Statistics panel that reviewed the food security measurement methods in 2004-06 recommended this change to reduce cognitive burden on respondents. Conforming changes in screening specifications were also made. NOTE: Question numbers were revised to reflect the new question order.  Follow up questions to the food sufficiency question (HH1) that were included in earlier versions of the module have been omitted.  User notes following the questionnaire have been revised to be consistent with current practice and with new labels for ranges of food security and food insecurity introduced by USDA in 2006.

Transition into Module (administered to all households):

These next questions are about the food eaten in your household in the last 12 months, since (current month) of last year and whether you were able to afford the food you need.

Optional USDA Food Sufficiency Question/Screener: Question HH1 (This question is optional. It is not used to calculate any of the food security scales. It may be used in conjunction with income as a preliminary screener to reduce respondent burden for high income households).

HH1. [IF ONE PERSON IN HOUSEHOLD, USE "I" IN PARENTHETICALS, OTHERWISE, USE "WE."] Which of these statements best describes the food eaten in your household in the last 12 months: — enough of the kinds of food (I/we) want to eat; —enough, but not always the kinds of food (I/we) want; —sometimes not enough to eat; or, —often not enough to eat?

[1] Enough of the kinds of food we want to eat

[2] Enough but not always the kinds of food we want

[3] Sometimes not enough to eat

[4] Often not enough to eat

[ ] DK or Refused

Household Stage 1: Questions HH2-HH4 (asked of all households; begin scale items).

[IF SINGLE ADULT IN HOUSEHOLD, USE "I," "MY," AND “YOU” IN

PARENTHETICALS; OTHERWISE, USE "WE," "OUR," AND "YOUR HOUSEHOLD."]

HH2. Now I’m going to read you several statements that people have made about their food situation. For these statements, please tell me whether the statement was often true, sometimes true, or never true for (you/your household) in the last 12 months—that is, since last (name of current month).

The first statement is “(I/We) worried whether (my/our) food would run out before (I/we) got money to buy more.” Was that often true, sometimes true, or never true for (you/your household) in the last 12 months?

[ ] Often true

[ ] Sometimes true

[ ] Never true

[ ] DK or Refused

HH3. “The food that (I/we) bought just didn’t last, and (I/we) didn’t have money to get more.” Was that often, sometimes, or never true for (you/your household) in the last 12 months? [ ] Often true [ ] Sometimes true

[ ] Never true [ ] DK or Refused

HH4. “(I/we) couldn’t afford to eat balanced meals.” Was that often, sometimes, or never true for (you/your household) in the last 12 months?

[ ] Often true

[ ] Sometimes true

[ ] Never true

[ ] DK or Refused Screener for Stage 2 Adult-Referenced Questions: If affirmative response (i.e., "often true" or "sometimes true") to one or more of Questions HH2-HH4, OR, response [3] or [4] to question HH1 (if administered), then continue to Adult Stage 2; otherwise, if children under age 18 are present in the household, skip to Child Stage 1, otherwise skip to End of Food Security Module.

NOTE: In a sample similar to that of the general U.S. population, about 20 percent of households (45 percent of households with incomes less than 185 percent of poverty line) will pass this screen and continue to Adult Stage 2.

Adult Stage 2: Questions AD1-AD4 (asked of households passing the screener for Stage 2 adult- referenced questions).

AD1. In the last 12 months, since last (name of current month), did (you/you or other adults in your household) ever cut the size of your meals or skip meals because there wasn't enough money for food?

[ ] Yes

[ ] No (Skip AD1a)

[ ] DK (Skip AD1a)

AD1a. [IF YES ABOVE, ASK] How often did this happen—almost every month, some months but not every month, or in only 1 or 2 months?

[ ] Almost every month

[ ] Some months but not every month

[ ] Only 1 or 2 months

[ ] DK

AD2. In the last 12 months, did you ever eat less than you felt you should because there wasn't enough money for food?

[ ] Yes

[ ] No [ ] DK

AD3. In the last 12 months, were you every hungry but didn't eat because there wasn't enough money for food?

[ ] Yes

[ ] No

[ ] DK

AD4. In the last 12 months, did you lose weight because there wasn't enough money for food?

[ ] Yes

[ ] No

[ ] DK

Screener for Stage 3 Adult-Referenced Questions: If affirmative response to one or more of questions AD1 through AD4, then continue to Adult Stage 3; otherwise, if children under age 18 are present in the household, skip to Child Stage 1, otherwise skip to End of Food Security Module.

NOTE: In a sample similar to that of the general U.S. population, about 8 percent of households (20 percent of households with incomes less than 185 percent of poverty line) will pass this screen and continue to Adult Stage 3.

Adult Stage 3: Questions AD5-AD5a (asked of households passing screener for Stage 3 adult-referenced questions).

AD5. In the last 12 months, did (you/you or other adults in your household) ever not eat for a whole day because there wasn't enough money for food?

[ ] Yes

[ ] No (Skip 12a) [ ] DK (Skip 12a)

AD5a. [IF YES ABOVE, ASK] How often did this happen—almost every month, some months but not every month, or in only 1 or 2 months?

[ ] DK

Child Stage 1: Questions CH1-CH3 (Transitions and questions CH1 and CH2 are administered to all households with children under age 18) Households with no child under age 18, skip to End of Food Security Module.

SELECT APPROPRIATE FILLS DEPENDING ON NUMBER OF ADULTS AND NUMBER OF CHILDREN IN THE HOUSEHOLD.

Transition into Child-Referenced Questions:

Now I'm going to read you several statements that people have made about the food situation of their children. For these statements, please tell me whether the statement was OFTEN true, SOMETIMES true, or NEVER true in the last 12 months for (your child/children living in the household who are under 18 years old).

CH1. “(I/we) relied on only a few kinds of low-cost food to feed (my/our) child/the children) because (I was/we were) running out of money to buy food.” Was that often, sometimes, or never true for (you/your household) in the last 12 months?

[ ] Often true

[ ] Sometimes true

[ ] Never true

[ ] DK or Refused CH2. “(I/We) couldn’t feed (my/our) child/the children) a balanced meal, because (I/we) couldn’t afford that.” Was that often, sometimes, or never true for (you/your household) in the last 12 months?

[ ] Often true

[ ] Sometimes true

[ ] Never true

[ ] DK or Refused

CH3. "(My/Our child was/The children were) not eating enough because (I/we) just couldn't afford enough food." Was that often, sometimes, or never true for (you/your household) in the last 12 months?

[ ] Often true

[ ] Sometimes true [ ] Never true

[ ] DK or Refused

Screener for Stage 2 Child Referenced Questions: If affirmative response (i.e., "often true" or "sometimes true") to one or more of questions CH1-CH3, then continue to Child Stage 2; otherwise skip to End of Food Security Module.

NOTE: In a sample similar to that of the general U.S. population, about 16 percent of households with children (35 percent of households with children with incomes less than 185 percent of poverty line) will pass this screen and continue to Child Stage 2.

Child Stage 2: Questions CH4-CH7 (asked of households passing the screener for stage 2 child- referenced questions).

NOTE: In Current Population Survey Food Security Supplements, question CH6 precedes question CH5.

CH4. In the last 12 months, since (current month) of last year, did you ever cut the size of (your child's/any of the children's) meals because there wasn't enough money for food?

[ ] Yes [ ] No

[ ] DK

CH5. In the last 12 months, did (CHILD’S NAME/any of the children) ever skip meals because there wasn't enough money for food?

[ ] Yes

[ ] No (Skip CH5a)

[ ] DK (Skip CH5a)

CH5a. [IF YES ABOVE ASK] How often did this happen—almost every month, some months but not every month, or in only 1 or 2 months?

[ ] DK

CH6. In the last 12 months, (was your child/were the children) ever hungry but you just couldn't afford more food?

[ ] Yes

[ ] No

[ ] DK

CH7. In the last 12 months, did (your child/any of the children) ever not eat for a whole day because there wasn't enough money for food?

[ ] Yes

[ ] No

[ ] DK END OF FOOD SECURITY MODULE

User Notes

(1) Coding Responses and Assessing Household Food Security Status:

Following is a brief overview of how to code responses and assess household food security status based on various standard scales. For detailed information on these procedures, refer to the Guide to Measuring Household Food Security, Revised 2000, and Measuring Children’s Food Security in U.S. Households, 1995- 1999. Both publications are available through the ERS Food Security in the United States Briefing Room.

Responses of “yes,” “often,” “sometimes,” “almost every month,” and “some months but not every month” are coded as affirmative. The sum of affirmative responses to a specified set of items is referred to as the household’s raw score on the scale comprising those items.

 Questions HH2 through CH7 comprise the U.S. Household Food Security Scale (questions HH2 through AD5a for households with no child present). Specification of food security status depends on raw score and whether there are children in the household (i.e., whether responses to child-referenced questions are included in the raw score). o For households with one or more children: . Raw score zero—High food security . Raw score 1-2—Marginal food security . Raw score 3-7—Low food security . Raw score 8-18—Very low food security o For households with no child present: . Raw score zero—High food security . Raw score 1-2—Marginal food security . Raw score 3-5—Low food security . Raw score 6-10—Very low food security

Households with high or marginal food security are classified as food secure. Those with low or very low food security are classified as food insecure.

 Questions HH2 through AD5a comprise the U.S. Adult Food Security Scale. . Raw score zero—High food security among adults . Raw score 1-2—Marginal food security among adults . Raw score 3-5—Low food security among adults . Raw score 6-10—Very low food security among adults

 Questions HH3 through AD3 comprise the six-item Short Module from which the Six-Item Food Security Scale can be calculated. . Raw score 0-1—High or marginal food security (raw score 1 may be considered marginal food security, but a large proportion of households that would be measured as having marginal food security using the household or adult scale will have raw score zero on the six- item scale) . Raw score 2-4—Low food security . Raw score 5-6—Very low food security

Questions CH1 through CH7 comprise the U.S. Children’s Food Security Scale. . Raw score 0-1—High or marginal food security among children (raw score 1 may be considered marginal food security, but it is not certain that all households with raw score zero have high food security among children because the scale does not include an assessment of the anxiety component of food insecurity) . Raw score 2-4—Low food security among children . Raw score 5-8—Very low food security among children

(2) Response Options: For interviewer-administered surveys, DK (“don’t know”) and “Refused” are blind responses—that is, they are not presented as response options, but marked if volunteered. For self-administered surveys, “don’t know” is presented as a response option.

(3) Screening: The two levels of screening for adult-referenced questions and one level for child-referenced questions are provided for surveys in which it is considered important to reduce respondent burden. In pilot surveys intended to validate the module in a new cultural, linguistic, or survey context, screening should be avoided if possible and all questions should be administered to all respondents.

To further reduce burden for higher income respondents, a preliminary screener may be constructed using question HH1 along with a household income measure. Households with income above twice the poverty threshold, AND who respond <1> to question HH1 may be skipped to the end of the module and classified as food secure. Use of this preliminary screener reduces total burden in a survey with many higher-income households, and the cost, in terms of accuracy in identifying food-insecure households, is not great. However, research has shown that a small proportion of the higher income households screened out by this procedure will register food insecurity if administered the full module. If question HH1 is not needed for research purposes, a preferred strategy is to omit HH1 and administer Adult Stage 1 of the module to all households and Child Stage 1 of the module to all households with children.

(4) 30-Day Reference Period: The questionnaire items may be modified to a 30-day reference period by changing the “last 12-month” references to “last 30 days.” In this case, items AD1a, AD5a, and CH5a must be changed to read as follows:

AD1a/AD5a/CH5a [IF YES ABOVE, ASK] In the last 30 days, how many days did this happen?

______days [ ] DK